Intelligent, data-driven solutions powered by machine learning to automate
processes, uncover insights, and enhance decision-making
Machine Learning
Predictive Models
Leverage data to forecast trends and user behavior accurately.
Automation Solutions
Streamline operations with smart, self-learning systems.
Data-Driven Insights
Unlock actionable insights through advanced ML algorithms.
Machine Learning: Model Design and Implementation
At Gatistavam Softech, we specialize in Machine Learning solutions—designing, developing, and deploying models tailored to your business needs.
This advanced AI technology is a key subset of Artificial Intelligence, centered on creating algorithms that learn from data to make accurate, data-driven predictions. It includes three main types: supervised, unsupervised, and reinforcement learning.
Gatistavam Systems can help you to :
- This subset of AI focuses on the development of algorithms that can learn from and make predictions on data.
- There are three main types: Supervised Learning, Unsupervised Learning, and Reinforcement Learning.
- Supervised learning involves training a model on labeled data and using the model to predict the output for new, unseen data.
- Unsupervised learning involves finding patterns or relationships in a dataset without having any prior labels.
- Reinforcement learning involves an agent learning how to interact with an environment in order to maximize a reward signal.
- Common evaluation metrics include accuracy, precision, recall, and F1 score.
- Overfitting occurs when a model is too complex and has learned the noise in the training data rather than the underlying pattern.
- Regularization is a technique used to prevent overfitting by adding a penalty term to the loss function during training.
- Feature engineering involves transforming raw data into a format that is more suitable for feeding into an intelligent model.
- Bias in intelligent systems refers to errors in the model that systematically favor or disfavor certain outcomes or groups.